Diffusion-geometric maximally stable component detection in deformable shapes
- Litman, R.; Bronstein, A. M.; Bronstein, Michael
- Maximally stable component detection is a very popular method for feature analysis in images, mainly due to its low computation cost and high repeatability. With the recent advance of feature-based methods in geometric shape analysis, there is significant interest in finding analogous approaches in the 3D world. In this paper, we formulate a diffusion-geometric framework for stable component detection in non-rigid 3D shapes, which can be used for geometric feature detection and description. A quantitative evaluation of our method on the SHREC'10 feature detection benchmark shows its potential as a source of high-quality features.
- Research areas:
- Type of Publication:
- MSER, stable regions, diffusion geometry, feature detection, shape analysis
- Computers and Graphics